Abstract: In allusion to the situation with missing measurements in which the sensor detecting probability is less than 1,a multi-sensor information fusion motivate target tracking algorithm based on missing measurements was proposed．First of all,based on the algorithm of residual error detection,the wild values from the observed data are distinguished,and accuracy of the measurement data can be determined during the state estimation process of dynamic system.Secondly,according to the improved EKF algorithm based on the conditions with missing measurements,the target motion state is estimated by use of every sensor node’s measurement data respectively,and then the multi-sensor optimal weighte fusion method is utilized to obtain the optimal estimation based on multi-sensor measurement data.Finally,the influence of the probability of the sensor detection on the filtering effect is obtained by simulation experiments using photoelectric sensors．And the simulation results demonstrate the effectiveness of the algorithm．Additionally,the algorithm’s trac-king accuracy is mostly approximate to the state estimation accuracy under the situation of complete measurements.

Key words: Maneuvering target tracking,Incomplete measurement,EKF,Multi-sensor information fusion